This research is to explain racial/ethnic disparities in breast cancer prognosis by examining patients' social network embeddedness. In addition to improving the explanation of the racial/ethnic gap, this approach will also help to establish effective intervention programs at community levels as discussed in this proposal. This project has four specific aims. (1) Generating a series of network characteristic indices for individual patients (or women referred for mammograms) for various statistical analyses. Based on network data collection, this project will construct a series of network variables so that each can be tested for any systematic effect on diverse dependent variables of breast cancer. These include variables for four dimensions of personal networks: cohesive support, information flow, dyadic support from the husband (or partner), and friends' health related attitudes, beliefs, knowledge, and behaviors. (2) Predicting the health related attitudes, beliefs, knowledge, and behaviors of the patient based on her relationships to her friends. By employing diverse social network models, this study examines the social mechanisms through which patients' attitudes (or knowledge and behaviors) is affected by their friends' attitude (knowledge and behaviors) based on phone interviews with the patients' friends. This will help to establish efficient and effective preventive strategies by revealing how people change their health related attitudes and behaviors. (3) Examining the hierarchical effects of two levels of social embeddedness and their interactions on cancer development such as getting mammograms. As a result of the specific design of the program as an integrated group, we can examine the hierarchical effects of two different levels of social embeddedness: 'micro-level patients' personal friendships' and 'macro-level neighborhood characteristics'. Hierarchical linear modeling will be employed to examine which level is important and how they interact. (4) Probing the age effect by analyzing social network embeddedness and combining it with racial/ethnic group disparities. This research will examine how elderly women's social networks are different from young women's and how those differences affect cancer development. Once age effect through social network embeddedness is revealed, the study will probe the racial/ethnic differences on the age effect.